• Rabia Tugba Kilic, Sedef Yildirimalp, and Cetin Sayaca.
• Rabia Tugba KILIC, Faculty of Health Sciences, Department of Physiotherapy, Ankara Yildirim Beyazit University, Turkey.
• Medicine (Baltimore). 2023 Nov 17; 102 (46): e35367e35367.

ObjectiveTo investigate the effect of protrusion amount on pain, lumbar mobility, physical dysfunction, and the cross-sectional area of the multifidus muscle in patients with lumbar disc herniation.Methods54 male patients aged 20 to 50 years were included in this study in 2 groups. The control group (n = 18) consisted of patients with disc herniation without nerve root compression, and the study group (n = 36) consisted of patients with lumbar disc herniation and nerve root compression in 3 subgroups according to the amount of protrusion. The multifidus muscle cross-sectional area and the amount of protrusion were measured using Magnetic Resonance Imaging. Pain intensity was measured using the Visual Pain Scale, physical dysfunction was measured using the Oswestry Disability Index, flexion-extension was measured with TiltMeter, and trunk rotation was measured with smartphone applications called iPhone Compass.ResultsThere were no differences in pain levels (P > .05), mean trunk rotation movements of the affected and unaffected sides (P = .001, P = .001, P = .983, and P = .954, respectively), Oswestry Disability Index results (P = .967), or cross-sectional area sizes of the multifidus muscle (P = .866, P = .552, P = .787, respectively). There was a difference between the groups in terms of the mean trunk flexion and extension movement values (P = .001). The regression analysis indicated that there was no significant correlation between the binary variables, and the models exhibited a low explanatory rate for the dependent variable.ConclusionA relationship has been identified between lumbar disc herniation and low back pain, lumbar movement limitation, and physical functionality. Nevertheless, subsequent to the regression analysis, it became evident that the binary variables did not exhibit a noteworthy relationship, leading to a decrease in the explanatory capacity of the models for the dependent variable. In forthcoming studies, it is advisable to contemplate the augmentation of the subject pool or the incorporation of multiple independent variables into the regression analysis as potential strategies to enhance the model capability in elucidating variations in the dependent variable.Copyright © 2023 the Author(s). Published by Wolters Kluwer Health, Inc.

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